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Author SHA1 Message Date
Doc
3ab553fb6d Fixes and a few additional helper functions 
- corrected the return type of a few functions to int
- Add DFWINDOW.TOOLS.getImageDiff to get how diff 2 images are
- Added complimentary lastNotBlack(X/Y)
- Increase blindly chosen preset "bottom_to_ignore". Wasnt enough when full screen.
- Fixed the sign/polarity of step sizes
- First attempt at calculating the size of the map. Probably wrong. Will replace when writing the map maker
- removed cv2.Stitcher stuff. Not what I needed
- Added some test_ functions for experimenting. Ignore.
 2026-01-13 09:52:09 -05:00
Doc
941eae5d57 test1 experiments. some optimizations 
- added self.test1 for experimenting cleaner
- began steps to calculate map size
- optimize several functions by moving from mean to max
 2026-01-13 04:07:19 -05:00
2 changed files with 158 additions and 47 deletions
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1
.gitignore vendored
View File

@@ -231,3 +231,4 @@ Thumbs.db
# experiment garbage
*.png
src/calib_info.json

204
src/df_tools/dfwindow.py
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@@ -1,4 +1,6 @@
import json
import time
import timeit
from pathlib import Path
import cv2
@@ -8,6 +10,8 @@ from loguru import logger
from .waytools import capActiveWindow, focusWindow, moveMouse
from .waytools import sendKey as _sendKey
# TODO: Consider type hinting images from cv2.typing import MatLike
class DFWINDOW:
class TOOLS:
@@ -29,24 +33,24 @@ class DFWINDOW:
) -> tuple[int, int]:
# Check the first (num_rows) rows at the top of the image,
# ignoring (ignore_cols) number of pixels at each end of teh line.
test_mean = np.mean(
test_max = np.max(
cv2.cvtColor(image_in[0:num_rows, ignore_cols:-ignore_cols], cv2.COLOR_BGR2GRAY),
axis=1, # get the mean along the x-axis
)
# TODO: handle when 0 results return
# Test the mean darkness, get the first row darker than 4
content_y = np.where(test_mean < mean_threshold)[0][0]
content_y = np.where(test_max < mean_threshold)[0][0]
_ignore_rows = max(ignore_rows, content_y + 1)
test_mean = np.mean(
test_max = np.max(
cv2.cvtColor(image_in[_ignore_rows:-_ignore_rows, 0:num_cols], cv2.COLOR_BGR2GRAY),
axis=0, # get the mean along the y-axis
)
content_x = np.where(test_mean < mean_threshold)[0][0]
content_x = np.where(test_max < mean_threshold)[0][0]
logger.debug(f"Content origin ({content_x}, {content_y})")
return (content_x, content_y)
return (int(content_x), int(content_y))
@staticmethod
def isRightBorder(img, num_columns=20, border_threshold: int = 10) -> bool:
@@ -58,6 +62,20 @@ class DFWINDOW:
# Are all pixels in the strip "black"
return not np.any(thresh)
@staticmethod
def getImageDiff(image1, image2, conversion=cv2.COLOR_BGR2GRAY) -> float:
# Diff size, very dif img
if image1.shape != image2.shape:
return float("inf")
grey1 = cv2.cvtColor(image1, conversion)
grey2 = cv2.cvtColor(image2, conversion)
# Apparently this is the Mean Squared Error (MES). Thanks Gemini (LLM)
err = np.sum((grey1.astype("float") - grey2.astype("float")) ** 2)
err /= float(grey1.shape[0] * grey1.shape[0])
return float(err)
@staticmethod
def isLeftBorder(img, num_columns=20, border_threshold: int = 10) -> bool:
# grab a greyscale strip to look at
@@ -89,20 +107,30 @@ class DFWINDOW:
return not np.any(thresh)
@staticmethod
def firstNotBlackX(img):
first_x = np.where(np.mean(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), axis=0) > 15)[0][0]
return first_x
def firstNotBlackX(img) -> int:
first_x = np.where(np.max(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), axis=0) > 5)[0][0]
return int(first_x)
@staticmethod
def firstNotBlackY(img):
first_y = np.where(np.mean(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), axis=1) > 15)[0][0]
return first_y
def lastNotBlackX(img) -> int:
first_x = np.where(np.max(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), axis=0) > 5)[0][-1]
return int(first_x)
bottom_to_ignore = 120
sleep_after_mouse = 0.2
sleep_after_key = 0.08
sleep_after_focus = 0.3
sleep_after_panning = 0.3
@staticmethod
def firstNotBlackY(img) -> int:
first_y = np.where(np.max(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), axis=1) > 5)[0][0]
return int(first_y)
@staticmethod
def lastNotBlackY(img) -> int:
first_y = np.where(np.max(cv2.cvtColor(img, cv2.COLOR_BGR2GRAY), axis=1) > 5)[0][-1]
return int(first_y)
bottom_to_ignore = 160
sleep_after_mouse = 0.2 # 2
sleep_after_key = 0.08 # 08
sleep_after_focus = 0.2 # 3
sleep_after_panning = 0.2 # 3
query_for_window = "dwarfort"
def __init__(self) -> None:
@@ -224,8 +252,8 @@ class DFWINDOW:
self.sendKeys("a", 30)
img = self.capWindow()
self._content_left, self._content_top = self.TOOLS.find_content_origin(img)
self._content_right = img.shape[1] - self._content_left
self._content_bottom = img.shape[0] - self.bottom_to_ignore
self._content_right = int(img.shape[1] - self._content_left)
self._content_bottom = int(img.shape[0] - self.bottom_to_ignore)
img = img[self._content_top : self._content_bottom, self._content_left : self._content_right] # pyright: ignore[reportOptionalSubscript]
logger.debug(f"Content width {self.contentWidth}. Content height {self.contentHeight}.")
@@ -239,8 +267,8 @@ class DFWINDOW:
img = self.capContent()
mx2 = self.TOOLS.firstNotBlackX(img)
my2 = self.TOOLS.firstNotBlackY(img)
self._step_size_x = mx2 - mx1
self._step_size_y = my2 - my1
self._step_size_x = mx1 - mx2
self._step_size_y = my1 - my2
logger.info(f"Step sizes calculated: x={self._step_size_x} and y={self._step_size_y}")
self.sendKeys("w")
self.sendKeys("a")
@@ -303,13 +331,6 @@ class DFWINDOW:
self._gridx = steps_right
self._gridy = steps_down
# TODO: Use seek tests to calculate mapsize in pixels
# at (0,0) save left_edge_offset and top_edge_offset
# at (max,max) save right_edge_offset and bottom_edge_offset
# width = (contentWidth - l_e_o) + (gridyx_max * _step_size_x) - abs(r_e_o)
# | <==|====|====|==> |
# (max*size) is too far, so we subract the ofset/border from the right map edge
# Test going to 0,0
self.setGridPos(0, 0)
time.sleep(self.sleep_after_panning)
@@ -318,6 +339,9 @@ class DFWINDOW:
logger.debug("Calibration error. Not at requested upper left of map")
raise Exception("Calibration error. Not at requested upper left of map")
cal_left_border = self.TOOLS.firstNotBlackX(img)
cal_top_border = self.TOOLS.firstNotBlackY(img)
# Test going to (max,max)
self.setGridPos(self.maxGridX, self.maxGridY)
time.sleep(self.sleep_after_panning)
@@ -326,31 +350,117 @@ class DFWINDOW:
logger.debug("Calibration error. Not at requested lower right of map")
raise Exception("Calibration error. Not at requested lower right of map")
cal_right_border = self.TOOLS.lastNotBlackX(img)
cal_bottom_border = self.TOOLS.lastNotBlackY(img)
# TODO: Use seek tests to calculate mapsize in pixels
# at (0,0) save left_edge_offset and top_edge_offset
# at (max,max) save right_edge_offset and bottom_edge_offset
# width = (contentWidth - l_e_o) + (gridyx_max * _step_size_x) - abs(r_e_o)
# | <==|====|====|==> |
# (max*size) is too far, so we subract the ofset/border from the right map edge
self._map_width = (
(img.shape[1] - cal_left_border) # Grid x = 0
+ ((self._gridx_max - 1) * self._step_size_x) # All the middle
+ cal_right_border # grid x = max
)
self._map_height = (
(img.shape[0] - cal_top_border) # Grid x = 0
+ ((self._gridy_max - 1) * self._step_size_y) # All the middle
+ cal_right_border # grid x = max
)
self.setGridPos(0, 0)
logger.debug(f"Map dimensions calculated as {self._map_width} x {self._map_height}")
logger.info(
f"Grid calibration complete. Grid steps ({self._gridy_max + 1},{self._gridy_max + 1}), step sizes({self._step_size_x},{self._step_size_y})"
)
def test1(self):
# rawimg = cv2.imread("./test_img.png")
rawimg = cv2.imread("grid_base_3.png")
img = rawimg[100 : -self.bottom_to_ignore - 70, 65:-65]
tlb = self.TOOLS.firstNotBlackX(img)
ttb = self.TOOLS.firstNotBlackY(img)
tt_setup = (
r"gc.enable() ; import cv2 ; import numpy as np ; timg = cv2.imread('./test_img.png', cv2.IMREAD_UNCHANGED)"
)
tt1 = timeit.Timer(
"np.where(np.mean(cv2.cvtColor(timg, cv2.COLOR_BGR2GRAY), axis=0) > 15)[0][0]",
setup=tt_setup,
)
tt2 = timeit.Timer(
"np.where(np.max(cv2.cvtColor(timg, cv2.COLOR_BGR2GRAY), axis=0) > 25)[0][0]",
setup=tt_setup,
)
tt3 = timeit.Timer(
"np.where(np.max(cv2.cvtColor(timg, cv2.COLOR_BGRA2GRAY), axis=0) > 25)[0][0]",
setup=tt_setup,
)
num_tests = 80
r1 = tt1.timeit(number=num_tests)
r2 = tt2.timeit(number=num_tests)
r3 = tt3.timeit(number=num_tests)
logger.debug("Pause here for testing")
def test_saveGrids(self):
savedir = Path()
savefile_base = "cached_grid"
savefile_ext = "png"
for x in range(0, self._gridx_max + 1):
for y in range(0, self._gridy_max):
self.setGridPos(x, y)
time.sleep(self.sleep_after_panning)
img = self.capContent()
savefilename = savedir.joinpath(f"{savefile_base}_{x}_{y}.{savefile_ext}")
cv2.imwrite(str(savefilename.resolve()), img)
calib_info = {
"gridx": int(self._gridx),
"gridy": int(self._gridy),
"gridx_max": int(self._gridx_max),
"gridy_max": int(self._gridy_max),
"step_size_x": int(self._step_size_x),
"step_size_y": int(self._step_size_y),
"content_top": int(self._content_top),
"content_bottom": int(self._content_bottom),
"content_left": int(self._content_left),
"content_right": int(self._content_right),
"map_height": int(self._map_height),
"map_width": int(self._map_width),
}
with open("./calib_info.json", "w") as fh:
json.dump(calib_info, fh)
def test_loadCalib(self):
with open("./calib_info.json") as fh:
calib_info = json.load(fh)
self._gridx = calib_info["gridx"]
self._gridy = calib_info["gridy"]
self._gridx_max = calib_info["gridx_max"]
self._gridy_max = calib_info["gridy_max"]
self._step_size_x = calib_info["step_size_x"]
self._step_size_y = calib_info["step_size_y"]
self._content_top = calib_info["content_top"]
self._content_bottom = calib_info["content_bottom"]
self._content_left = calib_info["content_left"]
self._content_right = calib_info["content_right"]
self._map_height = calib_info["map_height"]
self._map_width = calib_info["map_width"]
def getPanoramaMap(self):
# self.test1()
# return
self.calibrateGrid()
# Test getting pieces and stitching
stitcher = cv2.Stitcher.create(cv2.STITCHER_SCANS)
stitcher.setPanoConfidenceThresh(0.1) # Dont be confident
imgs_in_row = []
# Get a row
self.setGridPos(0, 0)
time.sleep(self.sleep_after_panning)
for x in range(0, self.maxGridX + 1, 3):
self.setGridPos(x, self.curGridY)
time.sleep(self.sleep_after_panning)
img = self.capContent()
if img.shape[2] == 4:
img = cv2.cvtColor(img, cv2.COLOR_BGRA2BGR)
imgs_in_row.append(img)
status, strip = stitcher.stitch(imgs_in_row)
logger.debug(f"{len(imgs_in_row)} images. {status=} {strip=} {status == cv2.Stitcher_OK}")
# self.test_saveGrids()
# self.test_loadCalib()
return None